Question

Explain the difference between deterministic and statistical models

Answer 1

Solution:

Difference between deterministic and statistical model

Deterministic model : A deterministic model is a mathematical model in which outcomes are determined through known relationships among the variables, without any room for random variation. A deterministic model never allow the elements of randomness. The deterministic model always produce the same output for a given input because there is no randomness involved in the deterministic model. It means a deterministic model provides the certain result as it don't make allowance to random error term. The examples of deterministic model are Newton law of motion, Molecular formula of water, known chemical reactions etc.

Statistical model : A statistical model is considered as probabilistic model and it always incorporate the randomness. A statistical model is always based on certain assumptions. A statistical model is the probabilistic model which is defined as the relationship between the random variables. As it incorporate the randomness it means that every time we run the model we can get different results even with the same initial conditions. A statistical model is always a mixture of deterministic elements and elements of randomness. Examples of this model are regression model, queueing model, Markov chain etc.

So, we can main say that the main basic difference between the both the models is the elements of randomness. Deterministic model does not allow the elements of randomness whereas, statistical model always have elements of randomness.